Structural families in loops of homologous proteins: automatic classification, modelling and application to antibodies

Do antibody CDR loops change conformation upon binding?

Antibodies have increasingly been developed as drugs with over 100 now licensed in the US or EU. During development, it is often necessary to increase or reduce the affinity of an antibody and rational attempts to do so rely on having a structure of the antibody-antigen complex often obtained by modeling. The antigen-binding site consists primarily of six loops known as complementarity-determining regions (CDRs), and an open question has been whether these loops change their conformation when they bind to an antigen. Existing surveys of antibody-antigen complex structures have only examined CDR conformational change in case studies or small-scale surveys. With an increasing number of antibodies where both free and complexed structures have been deposited in the Protein Data Bank, a large-scale survey of CDR conformational change during binding is now possible. To this end, we built a dataset, AbAgDb, that currently includes 177 antibodies with high-quality CDRs, each of which has at least one bound and one unbound structure. We analyzed the conformational change of the Cα backbone of each CDR upon binding and found that, in most cases, the CDRs (other than CDR-H3) show minimal movement, while 70.6% and 87% of CDR-H3s showed global Cα RMSD ≤ 1.0Å and ≤ 2.0Å, respectively. We also compared bound CDR conformations with the conformational space of unbound CDRs and found most of the bound conformations are included in the unbound conformational space. In future, our results will contribute to developing insights into antibodies and new methods for modeling and docking.

Structure-Based Optimization of Antibody-Based Biotherapeutics for Improved Developability: A Practical Guide for Molecular Modelers

A great effort to avoid known developability risks is now more often being made earlier during the lead candidate discovery and optimization phase of biotherapeutic drug development. Predictive computational strategies, used in the early stages of antibody discovery and development, to mitigate the risk of late-stage failure of antibody candidates, are highly valuable. Various structure-based methods exist for accurately predicting properties critical to developability, and, in this chapter, we discuss the history of their development and demonstrate how they can be used to filter large sets of candidates arising from target affinity screening and to optimize lead candidates for developability. Methods for modeling antibody structures from sequence and detecting post-translational modifications and chemical degradation liabilities are also discussed.

Structural Classification of CDR-H3 in Single-Domain VHH Antibodies

The immune systems protect vertebrates from foreign molecules or antigens, and antibodies are important mediators of this system. The sequences and structural features of antibodies vary depending on species. Many of antibodies from vertebrates, including camelids, have both heavy and light chain variable domains, but camelids also have antibodies that lack the light chains. In antibodies that lack light chains, the C-terminal variable region is called the V_HH domain. Antibodies recognize antigens through six complementarity-determining regions (CDRs). The third CDR of the heavy chain (CDR-H3) is at the center of the antigen-binding site and is diverse in terms of sequence and structure. Due to the importance of antibodies in basic science as well as in medical applications, there have been many studies of CDR-H3s of antibodies that possess both light and heavy chains. However, nature of CDR-H3s of single-domain V_HH antibodies is less well studied. In this chapter, we describe current knowledge of sequence-structure-function correlations of single-domain V_HH antibodies with emphasis on CDR-H3. Based on the 370 crystal structures in the Protein Data Bank, we also attempt structural classification of CDR-H3 in single-domain V_HH antibodies and discuss lessons learned from the ever-increasing number of the structures.

Coevolved Canonical Loops Conformations of Single-Domain Antibodies: A Tale of Three Pockets Playing Musical Chairs

Single-domain antibodies (sdAbs) are a promising class of biotherapeutics with unique structural traits within their paratope region. The distribution of canonical conformations explored by their complementarity determining region (CDR) loops differs to some extent from conventional two-chain Fv fragments of monoclonal antibodies (mAbs). In this study, we explored in detail the canonical structures of sdAb CDR-H1 and CDR-H2 loops and compared those with mAbs from the IGHV3 and IGHV1 gene families. We surveyed the antibody structures catalogued in SAbDab and clustered the CDR canonical loops in Cartesian space. While most of the sdAb clusters were sub-populations of previously defined canonical Fv conformations of CDR-H1 and CDR-H2, our stricter clustering approach defined narrower clusters in sequence-space. Meticulous visual inspection of sub-populations allowed a clearer understanding of sequence-structure relationships. The packing densities within structural pockets contacted by CDR-H1 and CDR-H2 canonical conformations were analyzed on the premise that these pockets cannot be left vacant as they would leave exposed supportive hydrophobic residues. The fine resolution of the canonical clusters defined here revealed unique signatures within these pockets, including distinct structural complementarities between CDR-H1 and CDR-H2 canonical clusters, which could not be perceived with the previous coarser clusters. We highlight examples where a single residue change in CDR-H1 sequence is sufficient to induce a dramatic population shift in CDR-H2 conformation. This suggests that preferences in combining CDR-H1 and CDR-H2 emerged naturally during antibody evolution, leading to preferred sets of conserved amino acids at key positions in the framework as well as within the CDR loops. We outline a game of musical chairs that is necessary to maintain the integrity of the antibody structures that arose during evolution. Our study also provides refined CDR-H1 and CDR-H2 structural templates for sdAb homology modeling that could be leveraged for improved antibody design.

Contrasting Modes of New World Arenavirus Neutralization by Immunization-Elicited Monoclonal Antibodies

Transmission of the New World hemorrhagic fever arenaviruses Junín virus (JUNV) and Machupo virus (MACV) to humans is facilitated, in part, by the interaction between the arenavirus GP1 glycoprotein and the human transferrin receptor 1 (hTfR1). We utilize a mouse model of live-attenuated immunization with envelope exchange viruses to isolate neutralizing monoclonal antibodies (NAbs) specific to JUNV GP1 and MACV GP1. Structures of two NAbs, termed JUN1 and MAC1, demonstrate that they neutralize through disruption of hTfR1 recognition. JUN1 utilizes a binding mode common to all characterized infection- and vaccine-elicited JUNV-specific NAbs, which involves mimicking hTfR1 binding through the insertion of a tyrosine into the receptor-binding site. In contrast, MAC1 undergoes a tyrosine-mediated mode of antigen recognition distinct from that used by the reported anti-JUNV NAbs and the only other characterized anti-MACV NAb. These data reveal the varied modes of GP1-specific recognition among New World arenaviruses by the antibody-mediated immune response. IMPORTANCE The GP1 subcomponent of the New World arenavirus GP is a primary target of the neutralizing antibody response, which has been shown to be effective in the prevention and treatment of infection. Here, we characterize the structural basis of the antibody-mediated immune response that arises from immunization of mice against Junín virus and Machupo virus, two rodent-borne zoonotic New World arenaviruses. We isolate a panel of GP1-specific monoclonal antibodies that recognize overlapping epitopes and exhibit neutralizing behavior, in vitro. Structural characterization of two of these antibodies indicates that antibody recognition likely interferes with GP1-mediated recognition of the transferrin receptor 1. These data provide molecular-level detail for a key region of vulnerability on the New World arenavirus surface and a blueprint for therapeutic antibody development.

Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics

Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly enabling the development of predictive models and computational tools for the "developability assessment" of antibody drug candidates. Here, we provide an overview of the antibody informatics tools applicable to the prediction of developability issues such as stability, aggregation, immunogenicity, and chemical degradation. We further evaluate the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Finally, we discuss the potential of developability guidelines based on in silico metrics that can be used for the assessment of antibody stability and manufacturability.

CDR loop interactions can determine heavy and light chain pairing preferences in bispecific antibodies

As the current biotherapeutic market is dominated by antibodies, the design of different antibody formats, like bispecific antibodies, is critical to the advancement of the field. In contrast to monovalent antibodies, which consist of two identical antigen-binding sites, bispecific antibodies can target two different epitopes by containing two different antigen-binding sites. Thus, the rise of new formats as successful therapeutics has reignited the interest in advancing and facilitating the efficient production of bispecific antibodies. Here, we investigate the influence of point mutations in the antigen-binding site, the paratope, on heavy and light chain pairing preferences by using molecular dynamics simulations. In agreement with experiments, we find that specific residues in the antibody variable domain (Fv), i.e., the complementarity-determining region (CDR) L3 and H3 loops, determine heavy and light chain pairing preferences. Excitingly, we observe substantial population shifts in CDR-H3 and CDR-L3 loop conformations in solution accompanied by a decrease in bispecific IgG yield. These conformational changes in the CDR3 loops induced by point mutations also influence all other CDR loop conformations and consequentially result in different CDR loop states in solution. However, besides their effect on the obtained CDR loop ensembles, point mutations also lead to distinct interaction patterns in the V_H-V_L interface. By comparing the interaction patterns among all investigated variants, we observe specific contacts in the interface that drive heavy and light chain pairing. Thus, these findings have broad implications in the field of antibody engineering and design because they provide a mechanistic understanding of antibody interfaces, by identifying critical factors driving the pairing preferences, and thus can help to advance the design of bispecific antibodies.

Kincore: a web resource for structural classification of protein kinases and their inhibitors

The active form of kinases is shared across different family members, as are several commonly observed inactive forms. We previously performed a clustering of the conformation of the activation loop of all protein kinase structures in the Protein Data Bank (PDB) into eight classes based on the dihedral angles that place the Phe side chain of the DFG motif at the N-terminus of the activation loop. Our clusters are strongly associated with the placement of the activation loop, the C-helix, and other structural elements of kinases. We present Kincore, a web resource providing access to our conformational assignments for kinase structures in the PDB. While other available databases provide conformational states or drug type but not both, KinCore includes the conformational state and the inhibitor type (Type 1, 1.5, 2, 3, allosteric) for each kinase chain. The user can query and browse the database using these attributes or determine the conformational labels of a kinase structure using the web server or a standalone program. The database and labeled structure files can be downloaded from the server. Kincore will help in understanding the conformational dynamics of these proteins and guide development of inhibitors targeting specific states. Kincore is available at http://dunbrack.fccc.edu/kincore.

Public Immunity: Evolutionary Spandrels for Pathway-Amplifying Protective Antibodies

Humoral immunity is seeded by affinity between the B cell receptor (BCR) and cognate antigen. While the BCR is a chimeric display of diverse antigen engagement solutions, we discuss its functional activity as an ‘innate-like’ immune receptor, wherein genetically hardwired antigen complementarity can serve as reproducible templates for pathway-amplifying otherwise immunologically recessive antibody responses. We propose that the capacity for germline reactivity to new antigen emerged as a set of evolutionary spandrels or coupled traits, which can now be exploited by rational vaccine design to focus humoral immunity upon conventionally immune-subdominant antibody targets. Accordingly, we suggest that evolutionary spandrels account for the necessary but unanticipated antigen reactivity of the germline antibody repertoire.

Paratope states in solution improve structure prediction and docking

Structure-based antibody design and accurate predictions of antibody-antigen interactions remain major challenges in computational biology. By using molecular dynamics simulations, we show that a single static X-ray structure is not sufficient to identify determinants of antibody-antigen recognition. Here, we investigate antibodies that undergo substantial conformational changes upon antigen binding and have been classified as difficult cases in an extensive benchmark for antibody-antigen docking. We present thermodynamics and transition kinetics of these conformational rearrangements and show that paratope states can be used to improve antibody-antigen docking. By using the unbound antibody X-ray structure as starting structure for molecular dynamics simulations, we retain a binding competent conformation substantially different to the unbound antibody X-ray structure. We also observe that the kinetically dominant antibody paratope conformations are chosen by the bound antigen conformation with the highest probability. Thus, we show that paratope states in solution can improve antibody-antigen docking and structure prediction.

Quantitative Description of Surface Complementarity of Antibody-Antigen Interfaces

Antibodies have the remarkable ability to recognise their cognate antigens with extraordinary affinity and specificity. Discerning the rules that define antibody-antigen recognition is a fundamental step in the rational design and engineering of functional antibodies with desired properties. In this study we apply the 3D Zernike formalism to the analysis of the surface properties of the antibody complementary determining regions (CDRs). Our results show that shape and electrostatic 3DZD descriptors of the surface of the CDRs are predictive of antigen specificity, with classification accuracy of 81% and area under the receiver operating characteristic curve (AUC) of 0.85. Additionally, while in terms of surface size, solvent accessibility and amino acid composition, antibody epitopes are typically not distinguishable from non-epitope, solvent-exposed regions of the antigen, the 3DZD descriptors detect significantly higher surface complementarity to the paratope, and are able to predict correct paratope-epitope interaction with an AUC = 0.75.

Germline-Dependent Antibody Paratope States and Pairing Specific VH-VL Interface Dynamics

Antibodies have emerged as one of the fastest growing classes of biotherapeutic proteins. To improve the rational design of antibodies, we investigate the conformational diversity of 16 different germline combinations, which are composed of 4 different kappa light chains paired with 4 different heavy chains. In this study, we systematically show that different heavy and light chain pairings strongly influence the paratope, interdomain interaction patterns and the relative V_H-V_L interface orientations. We observe changes in conformational diversity and substantial population shifts of the complementarity determining region (CDR) loops, resulting in distinct dominant solution structures and differently favored canonical structures. Additionally, we identify conformational changes in the structural diversity of the CDR-H3 loop upon different heavy and light chain pairings, as well as upon changes in sequence and structure of the neighboring CDR loops, despite having an identical CDR-H3 loop amino acid sequence. These results can also be transferred to all CDR loops and to the relative V_H-V_L orientation, as certain paratope states favor distinct interface angle distributions. Furthermore, we directly compare the timescales of sidechain rearrangements with the well-described transition kinetics of conformational changes in the backbone of the CDR loops. We show that sidechain flexibilities are strongly affected by distinct heavy and light chain pairings and decipher germline-specific structural features co-determining stability. These findings reveal that all CDR loops are strongly correlated and that distinct heavy and light chain pairings can result in different paratope states in solution, defined by a characteristic combination of CDR loop conformations and V_H-V_L interface orientations. Thus, these results have broad implications in the field of antibody engineering, as they clearly show the importance of considering paired heavy and light chains to understand the antibody binding site, which is one of the key aspects in the design of therapeutics.

A Single Human VH-gene Allows for a Broad-Spectrum Antibody Response Targeting Bacterial Lipopolysaccharides in the Blood

B cell receptors (BCRs) display a combination of variable (V)-gene-encoded complementarity determining regions (CDRs) and adaptive/hypervariable CDR3 loops to engage antigens. It has long been proposed that the former tune for recognition of pathogens or groups of pathogens. To experimentally evaluate this within the human antibody repertoire, we perform immune challenges in transgenic mice that bear diverse human CDR3 and light chains but are constrained to different human V_H-genes. We find that, of six commonly deployed V_H sequences, only those CDRs encoded by IGHV1-2^∗02 enable polyclonal antibody responses against bacterial lipopolysaccharide (LPS) when introduced to the bloodstream. The LPS is from diverse strains of gram-negative bacteria, and the V_H-gene-dependent responses are directed against the non-variable and universal saccrolipid substructure of this antigen. This reveals a broad-spectrum anti-LPS response in which germline-encoded CDRs naturally hardwire the human antibody repertoire for recognition of a conserved microbial target.

Ensembles in solution as a new paradigm for antibody structure prediction and design

The rise of antibodies as a promising and rapidly growing class of biotherapeutic proteins has motivated numerous studies to characterize and understand antibody structures. In the past decades, the number of antibody crystal structures increased substantially, which revolutionized the atomistic understanding of antibody functions. Even though numerous static structures are known, various biophysical properties of antibodies (i.e., specificity, hydrophobicity and stability) are governed by their dynamic character. Additionally, the importance of high-quality structures in structure–function relationship studies has substantially increased. These structure–function relationship studies have also created a demand for precise homology models of antibody structures, which allow rational antibody design and engineering when no crystal structure is available. Here, we discuss various aspects and challenges in antibody design and extend the paradigm of describing antibodies with only a single static structure to characterizing them as dynamic ensembles in solution.

Mutation of Framework Residue H71 Results in Different Antibody Paratope States in Solution

Characterizing and understanding the antibody binding interface have become a pre-requisite for rational antibody design and engineering. The antigen-binding site is formed by six hypervariable loops, known as the complementarity determining regions (CDRs) and by the relative interdomain orientation (V_H-V_L). Antibody CDR loops with a certain sequence have been thought to be limited to a single static canonical conformation determining their binding properties. However, it has been shown that antibodies exist as ensembles of multiple paratope states, which are defined by a characteristic combination of CDR loop conformations and interdomain orientations. In this study, we thermodynamically and kinetically characterize the prominent role of residue 71^H (Chothia nomenclature), which does not only codetermine the canonical conformation of the CDR-H2 loop but also results in changes in conformational diversity and population shifts of the CDR-H1 and CDR-H3 loop. As all CDR loop movements are correlated, conformational rearrangements of the heavy chain CDR loops also induce conformational changes in the CDR-L1, CDR-L2, and CDR-L3 loop. These overall conformational changes of the CDR loops also influence the interface angle distributions, consequentially leading to different paratope states in solution. Thus, the type of residue of 71^H, either an alanine or an arginine, not only influences the CDR-H2 loop ensembles, but co-determines the paratope states in solution. Characterization of the functional consequences of mutations of residue 71^H on the paratope states and interface orientations has broad implications in the field of antibody engineering.

Antibody CDR loops as ensembles in solution vs. canonical clusters from X-ray structures

In the past decade, the relevance of antibodies as therapeutics has increased substantially. Therefore, structural and functional characterization, in particular of the complementarity-determining regions (CDRs), is crucial to the design and engineering of antibodies with unique binding properties. Various studies have focused on classifying the CDR loops into a small set of main-chain conformations to facilitate antibody design by assuming that certain sequences can only adopt a limited number of conformations. Here, we present a kinetic classification of CDR loop structures as ensembles in solution. Using molecular dynamics simulations in combination with strong experimental structural information, we observe conformational transitions between canonical clusters and additional dominant solution structures in the micro-to-millisecond timescale for all CDR loops, independent of length and sequence composition. Besides identifying all relevant conformations in solution, our results revealed that various canonical cluster medians actually belong to the same kinetic minimum. Additionally, we reconstruct the kinetics and probabilities of the conformational transitions between canonical clusters, and thereby extend the model of static canonical structures to reveal a dynamic conformational ensemble in solution as a new paradigm in the field of antibody structure design.

Abbreviations: CDR: Complementary-determining region; Fv: Antibody variable fragment; PCCA: Perron cluster analysis; tICA: Time-lagged independent component analysis; V_H: Heavy chain variable region; V_L: Light chain variable region

Protein structure analysis of the interactions between SARS-CoV-2 spike protein and the human ACE2 receptor: from conformational changes to novel neutralizing antibodies

The recent severe acute respiratory syndrome, known as Coronavirus Disease 2019 (COVID-19) has spread so much rapidly and severely to induce World Health Organization (WHO) to declare a state of emergency over the new coronavirus SARS-CoV-2 pandemic. While several countries have chosen the almost complete lock-down for slowing down SARS-CoV-2 spread, the scientific community is called to respond to the devastating outbreak by identifying new tools for diagnosis and treatment of the dangerous COVID-19. With this aim, we performed an in silico comparative modeling analysis, which allows gaining new insights into the main conformational changes occurring in the SARS-CoV-2 spike protein, at the level of the receptor-binding domain (RBD), along interactions with human cells angiotensin-converting enzyme 2 (ACE2) receptor, that favor human cell invasion. Furthermore, our analysis provides (1) an ideal pipeline to identify already characterized antibodies that might target SARS-CoV-2 spike RBD, aiming to prevent interactions with the human ACE2, and (2) instructions for building new possible neutralizing antibodies, according to chemical/physical space restraints and complementary determining regions (CDR) mutagenesis of the identified existing antibodies. The proposed antibodies show in silico high affinity for SARS-CoV-2 spike RBD and can be used as reference antibodies also for building new high-affinity antibodies against present and future coronaviruses able to invade human cells through interactions of their spike proteins with the human ACE2. More in general, our analysis provides indications for the set-up of the right biological molecular context for investigating spike RBD-ACE2 interactions for the development of new vaccines, diagnostic kits, and other treatments based on the targeting of SARS-CoV-2 spike protein.

Surprisingly Fast Interface and Elbow Angle Dynamics of Antigen-Binding Fragments

Fab consist of a heavy and light chain and can be subdivided into a variable (V H and V L ) and a constant region (C H 1 and C L ). The variable region contains the complementarity-determining region (CDR), which is formed by six hypervariable loops, shaping the antigen binding site, the paratope. Apart from the CDR loops, both the elbow angle and the relative interdomain orientations of the V H -V L and the C H 1-C L domains influence the shape of the paratope. Thus, characterization of the interface and elbow angle dynamics is essential to antigen specificity. We studied nine antigen-binding fragments (Fab) to investigate the influence of affinity maturation, antibody humanization, and different light-chain types on the interface and elbow angle dynamics. While the CDR loops reveal conformational transitions in the micro-to-millisecond timescale, both the interface and elbow angle dynamics occur on the low nanosecond timescale. Upon affinity maturation, we observe a substantial rigidification of the V H and V L interdomain and elbow-angle flexibility, reflected in a narrower and more distinct distribution. Antibody humanization describes the process of grafting non-human CDR loops onto a representative human framework. As the antibody framework changes upon humanization, we investigated if both the interface and the elbow angle distributions are changed or shifted. The results clearly showed a substantial shift in the relative V H -V L distributions upon antibody humanization, indicating that different frameworks favor distinct interface orientations. Additionally, the interface and elbow angle dynamics of five antibody fragments with different light-chain types are included, because of their strong differences in elbow angles. For these five examples, we clearly see a high variability and flexibility in both interface and elbow angle dynamics, highlighting the fact that Fab interface orientations and elbow angles interconvert between each other in the low nanosecond timescale. Understanding how the relative interdomain orientations and the elbow angle influence antigen specificity, affinity, and stability has broad implications in the field of antibody modeling and engineering.

Antibodies exhibit multiple paratope states influencing VH-VL domain orientations

In the last decades, antibodies have emerged as one of the most important and successful classes of biopharmaceuticals. The highest variability and diversity of an antibody is concentrated on six hypervariable loops, also known as complementarity determining regions (CDRs) shaping the antigen-binding site, the paratope. Whereas it was assumed that certain sequences can only adopt a limited set of backbone conformations, in this study we present a kinetic classification of several paratope states in solution. Using molecular dynamics simulations in combination with experimental structural information we capture the involved conformational transitions between different canonical clusters and additional dominant solution structures occurring in the micro-to-millisecond timescale. Furthermore, we observe a strong correlation of CDR loop movements. Another important aspect when characterizing different paratope states is the relative VH/VL orientation and the influence of the distinct CDR loop states on the VH/VL interface. Conformational rearrangements of the CDR loops do not only have an effect on the relative VH/VL orientations, but also influence in some cases the elbow-angle dynamics and shift the respective distributions. Thus, our results show that antibodies exist as several interconverting paratope states, each contributing to the antibody's properties.

Computational approaches to therapeutic antibody design: established methods and emerging trends

Antibodies are proteins that recognize the molecular surfaces of potentially noxious molecules to mount an adaptive immune response or, in the case of autoimmune diseases, molecules that are part of healthy cells and tissues. Due to their binding versatility, antibodies are currently the largest class of biotherapeutics, with five monoclonal antibodies ranked in the top 10 blockbuster drugs. Computational advances in protein modelling and design can have a tangible impact on antibody-based therapeutic development. Antibody-specific computational protocols currently benefit from an increasing volume of data provided by next generation sequencing and application to related drug modalities based on traditional antibodies, such as nanobodies. Here we present a structured overview of available databases, methods and emerging trends in computational antibody analysis and contextualize them towards the engineering of candidate antibody therapeutics.

Protein structure analysis of the interactions between SARS-CoV-2 spike protein and the human ACE2 receptor: from conformational changes to novel neutralizing antibodies

The recent severe acute respiratory syndrome, known as Coronavirus Disease 2019 (COVID-19) has spread so much rapidly and severely to induce World Health Organization (WHO) to declare a state of emergency over the new coronavirus SARS-CoV-2 pandemic. While several countries have chosen the almost complete lock-down for slowing down SARS-CoV-2 spread, the scientific community is called to respond to the devastating outbreak by identifying new tools for diagnosis and treatment of the dangerous COVID-19. With this aim, we performed an in silico comparative modeling analysis, which allows gaining new insights into the main conformational changes occurring in the SARS-CoV-2 spike protein, at the level of the receptor-binding domain (RBD), along interactions with human cells angiotensin-converting enzyme 2 (ACE2) receptor, that favor human cell invasion. Furthermore, our analysis provides (1) an ideal pipeline to identify already characterized antibodies that might target SARS-CoV-2 spike RBD, aiming to prevent interactions with the human ACE2, and (2) instructions for building new possible neutralizing antibodies, according to chemical/physical space restraints and complementary determining regions (CDR) mutagenesis of the identified existing antibodies. The proposed antibodies show in silico high affinity for SARS-CoV-2 spike RBD and can be used as reference antibodies also for building new high-affinity antibodies against present and future coronaviruses able to invade human cells through interactions of their spike proteins with the human ACE2. More in general, our analysis provides indications for the set-up of the right biological molecular context for investigating spike RBD–ACE2 interactions for the development of new vaccines, diagnostic kits, and other treatments based on the targeting of SARS-CoV-2 spike protein.

Discrete analysis of camelid variable domains: sequences, structures, and in-silico structure prediction

Antigen binding by antibodies requires precise orientation of the complementarity- determining region (CDR) loops in the variable domain to establish the correct contact surface. Members of the family Camelidae have a modified form of immunoglobulin gamma (IgG) with only heavy chains, called Heavy Chain only Antibodies (HCAb). Antigen binding in HCAbs is mediated by only three CDR loops from the single variable domain (V_HH) at the N-terminus of each heavy chain. This feature of the V_HH, along with their other important features, e.g., easy expression, small size, thermo-stability and hydrophilicity, made them promising candidates for therapeutics and diagnostics. Thus, to design better V_HH domains, it is important to thoroughly understand their sequence and structure characteristics and relationship. In this study, sequence characteristics of V_HH domains have been analysed in depth, along with their structural features using innovative approaches, namely a structural alphabet. An elaborate summary of various studies proposing structural models of V_HH domains showed diversity in the algorithms used. Finally, a case study to elucidate the differences in structural models from single and multiple templates is presented. In this case study, along with the above-mentioned aspects of V_HH, an exciting view of various factors in structure prediction of V_HH, like template framework selection, is also discussed.

Antibody Clustering Using a Machine Learning Pipeline that Fuses Genetic, Structural, and Physicochemical Properties

Antibody V domain clustering is of paramount importance to a repertoire of immunology-related areas. Although several approaches have been proposed for antibody clustering, still no consensus has been reached. Numerous attempts use information from genes, protein sequences, 3D structures, and 3D surfaces in an effort to elucidate unknown action mechanisms directly related to their function and to either link them directly to diseases or drive the discovery of new medicines, such as antibody drug conjugates (ADC). Herein, we describe a new V domain antibody clustering method based on the comparison of the interaction sites between each antibody and its antigen. A more specific clustering analysis of the antibody's V domain was provided using deep learning and data mining techniques. The multidimensional information was extracted from the structural resolved antibodies when they were captured to interact with other proteins. The available 3D structures of protein antigen-antibody (Ag-Ab) interfaces contain information about how antibody V domains recognize antigens as well as about which amino acids are involved in the recognition. As such, the antibody surface holds information about antigens' folding that reside with the Ab-Ag interface residues and how they interact. In order to gain insight into the nature of such interactions, we propose a new simple philosophy to transform the conserved framework (fragment regions, complementarity-determining regions) of antibody V domain in a binary form using structural features of antibody-antigen interactions, toward identifying new antibody signatures in V domain binding activity. Finally, an advanced three-level hybrid classification scheme has been set for clustering antibodies in subgroups, which can combine the information from the protein sequences, the three-dimensional structures, and specific "key patterns" of recognized interactions. The clusters provide multilevel information about antibodies and antibody-antigen complexes.

Antibody Structure and Function: The Basis for Engineering Therapeutics

Antibodies and antibody-derived macromolecules have established themselves as the mainstay in protein-based therapeutic molecules (biologics). Our knowledge of the structure–function relationships of antibodies provides a platform for protein engineering that has been exploited to generate a wide range of biologics for a host of therapeutic indications. In this review, our basic understanding of the antibody structure is described along with how that knowledge has leveraged the engineering of antibody and antibody-related therapeutics having the appropriate antigen affinity, effector function, and biophysical properties. The platforms examined include the development of antibodies, antibody fragments, bispecific antibody, and antibody fusion products, whose efficacy and manufacturability can be improved via humanization, affinity modulation, and stability enhancement. We also review the design and selection of binding arms, and avidity modulation. Different strategies of preparing bispecific and multispecific molecules for an array of therapeutic applications are included.

A structural basis for antibody-mediated neutralization of Nipah virus reveals a site of vulnerability at the fusion glycoprotein apex

Nipah virus (NiV) is a highly pathogenic paramyxovirus that causes frequent outbreaks of severe neurologic and respiratory disease in humans with high case fatality rates. The 2 glycoproteins displayed on the surface of the virus, NiV-G and NiV-F, mediate host-cell attachment and membrane fusion, respectively, and are targets of the host antibody response. Here, we provide a molecular basis for neutralization of NiV through antibody-mediated targeting of NiV-F. Structural characterization of a neutralizing antibody (nAb) in complex with trimeric prefusion NiV-F reveals an epitope at the membrane-distal domain III (DIII) of the molecule, a region that undergoes substantial refolding during host-cell entry. The epitope of this monoclonal antibody (mAb66) is primarily protein-specific and we observe that glycosylation at the periphery of the interface likely does not inhibit mAb66 binding to NiV-F. Further characterization reveals that a Hendra virus-F-specific nAb (mAb36) and many antibodies in an antihenipavirus-F polyclonal antibody mixture (pAb835) also target this region of the molecule. Integrated with previously reported paramyxovirus F-nAb structures, these data support a model whereby the membrane-distal region of the F protein is targeted by the antibody-mediated immune response across henipaviruses. Notably, our domain-specific sequence analysis reveals no evidence of selective pressure at this region of the molecule, suggestive that functional constraints prevent immune-driven sequence variation. Combined, our data reveal the membrane-distal region of NiV-F as a site of vulnerability on the NiV surface.

Comparative Analysis of the CDR Loops of Antigen Receptors

The adaptive immune system uses two main types of antigen receptors: T-cell receptors (TCRs) and antibodies. While both proteins share a globally similar β-sandwich architecture, TCRs are specialized to recognize peptide antigens in the binding groove of the major histocompatibility complex, while antibodies can bind an almost infinite range of molecules. For both proteins, the main determinants of target recognition are the complementarity-determining region (CDR) loops. Five of the six CDRs adopt a limited number of backbone conformations, known as the "canonical classes"; the remaining CDR (β3in TCRs and H3 in antibodies) is more structurally diverse. In this paper, we first update the definition of canonical forms in TCRs, build an auto-updating sequence-based prediction tool (available at http://opig.stats.ox.ac.uk/resources) and demonstrate its application on large scale sequencing studies. Given the global similarity of TCRs and antibodies, we then examine the structural similarity of their CDRs. We find that TCR and antibody CDRs tend to have different length distributions, and where they have similar lengths, they mostly occupy distinct structural spaces. In the rare cases where we found structural similarity, the underlying sequence patterns for the TCR and antibody version are different. Finally, where multiple structures have been solved for the same CDR sequence, the structural variability in TCR loops is higher than that in antibodies, suggesting TCR CDRs are more flexible. These structural differences between TCR and antibody CDRs may be important to their different biological functions.

Phage Display Libraries for Antibody Therapeutic Discovery and Development

Phage display technology has played a key role in the remarkable progress of discovering and optimizing antibodies for diverse applications, particularly antibody-based drugs. This technology was initially developed by George Smith in the mid-1980s and applied by John McCafferty and Gregory Winter to antibody engineering at the beginning of 1990s. Here, we compare nine phage display antibody libraries published in the last decade, which represent the state of the art in the discovery and development of therapeutic antibodies using phage display. We first discuss the quality of the libraries and the diverse types of antibody repertoires used as substrates to build the libraries, i.e., naïve, synthetic, and semisynthetic. Second, we review the performance of the libraries in terms of the number of positive clones per panning, hit rate, affinity, and developability of the selected antibodies. Finally, we highlight current opportunities and challenges pertaining to phage display platforms and related display technologies.

Fab Fragment of VHH-Based Antibody Netakimab: Crystal Structure and Modeling Interaction with Cytokine IL-17A

Interleukin 17A (IL-17A) is a proinflammatory cytokine produced by Th17 cells. Antibody BCD-085 (netakimab) against human IL-17A is one of the new inhibitors of this cytokine. In netakimab, the VH domain is replaced by the VHH domain of Lama glama possessing a long complementarity determining region (CDR-H3) in its heavy chain. Here we demonstrate the high affinity of IL-17A to the Fab fragment of netakimab and to its integral part, the VHH domain. We have determined the crystal structure of the Fab fragment of netakimab at 1.9 Å resolution. High variability in the orientation of light and heavy chains of the Fab fragment of netakimab was shown, which is determined by the peculiarity of the structural organization of the CDR-H3. As the high conformational plasticity of the molecule hampers modeling the Fab fragment of netakimab complexed to IL-17A, we have carried out modeling the complex between the antigen and the integral part of the Fab fragment, the VHH domain. We explain the high netakimab Fab fragment affinity for IL-17A by a large number of protein–protein contacts due to additional interactions between CDR-H3 and the cytokine dimer.

Understanding the Significance and Implications of Antibody Numbering and Antigen-Binding Surface/Residue Definition

Monoclonal antibodies are playing an increasing role in both human and animal health. Different strategies of protein and chemical engineering, including humanization techniques of non-human antibodies were applied successfully to optimize clinical performances of antibodies. Despite the emergence of techniques allowing the development of fully human antibodies such as transgenic Xeno-mice, antibody humanization remains a standard procedure for therapeutic antibodies. An important prerequisite for antibody humanization requires standardized numbering methods to define precisely complementary determining regions (CDR), frameworks and residues from the light and heavy chains that affect the binding affinity and/or specificity of the antibody-antigen interaction. The recently generated deep-sequencing data and the increasing number of solved three-dimensional structures of antibodies from human and non-human origins have led to the emergence of numerous databases. However, these different databases use different numbering conventions and CDR definitions. In addition, the large fluctuation of the variable chain lengths, especially in CDR3 of heavy chains (CDRH3), hardly complicates the comparison and analysis of antibody sequences and the identification of the antigen binding residues. This review compares and discusses the different numbering schemes and "CDR" definition that were established up to date. Furthermore, it summarizes concepts and strategies used for numbering residues of antibodies and CDR residues identification. Finally, it discusses the importance of specific sets of residues in the binding affinity and/or specificity of immunoglobulins.

AbDb: antibody structure database-a database of PDB-derived antibody structures

In order to analyse structures of proteins of a particular class, these need to be extracted from Protein Data Bank (PDB) files. In the case of antibodies, there are a number of special considerations: (i) identifying antibodies in the PDB is not trivial, (ii) they may be crystallized with or without antigen, (iii) for analysis purposes, one is normally only interested in the Fv region of the antibody, (iv) structural analysis of epitopes, in particular, requires individual antibody–antigen complexes from a PDB file which may contain multiple copies of the same, or different, antibodies and (v) standard numbering schemes should be applied. Consequently, there is a need for a specialist resource containing pre-numbered non-redundant antibody Fv structures with their cognate antigens. We have created an automatically updated resource, AbDb, which collects the Fv regions from antibody structures using information from our SACS database which summarizes antibody structures from the PDB. PDB files containing multiple structures are split and numbered and each antibody structure is associated with its antigen where available. Antibody structures with only light or heavy chains have also been processed and sequences of antibodies are compared to identify multiple structures of the same antibody. The data may be queried on the basis of PDB code, or the name or species of the antibody or antigen, and the complete datasets may be downloaded.

Database URL: www.bioinf.org.uk/abs/abdb/

Generation and characterisation of recombinant FMDV antibodies: Applications for advancing diagnostic and laboratory assays

Foot-and-mouth disease (FMD) affects economically important livestock and is one of the most contagious viral diseases. The most commonly used FMD diagnostic assay is a sandwich ELISA. However, the main disadvantage of this ELISA is that it requires anti-FMD virus (FMDV) serotype-specific antibodies raised in small animals. This problem can be, in part, overcome by using anti-FMDV monoclonal antibodies (MAbs) as detecting reagents. However, the long-term use of MAbs may be problematic and they may need to be replaced. Here we have constructed chimeric antibodies (mouse/rabbit D9) and Fabs (fragment antigen-binding) (mouse/cattle D9) using the Fv (fragment variable) regions of a mouse MAb, D9 (MAb D9), which recognises type O FMDV. The mouse/rabbit D9 chimeric antibody retained the FMDV serotype-specificity of MAb D9 and performed well in a FMDV detection ELISA as well as in routine laboratory assays. Cryo-electron microscopy analysis confirmed engagement with antigenic site 1 and peptide competition studies identified the aspartic acid at residue VP1 147 as a novel component of the D9 epitope. This chimeric expression approach is a simple but effective way to preserve valuable FMDV antibodies, and has the potential for unlimited generation of antibodies and antibody fragments in recombinant systems with the concomitant positive impacts on the 3Rs (Replacement, Reduction and Refinement) principles.

In Silico Methods in Antibody Design

Antibody therapies with high efficiency and low toxicity are becoming one of the major approaches in antibody therapeutics. Based on high-throughput sequencing and increasing experimental structures of antibodies/antibody-antigen complexes, computational approaches can predict antibody/antigen structures, engineering the function of antibodies and design antibody-antigen complexes with improved properties. This review summarizes recent progress in the field of in silico design of antibodies, including antibody structure modeling, antibody-antigen complex prediction, antibody stability evaluation, and allosteric effects in antibodies and functions. We listed the cases in which these methods have helped experimental studies to improve the affinities and physicochemical properties of antibodies. We emphasized how the molecular dynamics unveiled the allosteric effects during antibody-antigen recognition and antibody-effector recognition.

RosettaAntibodyDesign (RAbD): A general framework for computational antibody design

A structural-bioinformatics-based computational methodology and framework have been developed for the design of antibodies to targets of interest. RosettaAntibodyDesign (RAbD) samples the diverse sequence, structure, and binding space of an antibody to an antigen in highly customizable protocols for the design of antibodies in a broad range of applications. The program samples antibody sequences and structures by grafting structures from a widely accepted set of the canonical clusters of CDRs (North et al., J. Mol. Biol., 406:228-256, 2011). It then performs sequence design according to amino acid sequence profiles of each cluster, and samples CDR backbones using a flexible-backbone design protocol incorporating cluster-based CDR constraints. Starting from an existing experimental or computationally modeled antigen-antibody structure, RAbD can be used to redesign a single CDR or multiple CDRs with loops of different length, conformation, and sequence. We rigorously benchmarked RAbD on a set of 60 diverse antibody-antigen complexes, using two design strategies-optimizing total Rosetta energy and optimizing interface energy alone. We utilized two novel metrics for measuring success in computational protein design. The design risk ratio (DRR) is equal to the frequency of recovery of native CDR lengths and clusters divided by the frequency of sampling of those features during the Monte Carlo design procedure. Ratios greater than 1.0 indicate that the design process is picking out the native more frequently than expected from their sampled rate. We achieved DRRs for the non-H3 CDRs of between 2.4 and 4.0. The antigen risk ratio (ARR) is the ratio of frequencies of the native amino acid types, CDR lengths, and clusters in the output decoys for simulations performed in the presence and absence of the antigen. For CDRs, we achieved cluster ARRs as high as 2.5 for L1 and 1.5 for H2. For sequence design simulations without CDR grafting, the overall recovery for the native amino acid types for residues that contact the antigen in the native structures was 72% in simulations performed in the presence of the antigen and 48% in simulations performed without the antigen, for an ARR of 1.5. For the non-contacting residues, the ARR was 1.08. This shows that the sequence profiles are able to maintain the amino acid types of these conserved, buried sites, while recovery of the exposed, contacting residues requires the presence of the antigen-antibody interface. We tested RAbD experimentally on both a lambda and kappa antibody-antigen complex, successfully improving their affinities 10 to 50 fold by replacing individual CDRs of the native antibody with new CDR lengths and clusters.

How B-Cell Receptor Repertoire Sequencing Can Be Enriched with Structural Antibody Data

Next-generation sequencing of immunoglobulin gene repertoires (Ig-seq) allows the investigation of large-scale antibody dynamics at a sequence level. However, structural information, a crucial descriptor of antibody binding capability, is not collected in Ig-seq protocols. Developing systematic relationships between the antibody sequence information gathered from Ig-seq and low-throughput techniques such as X-ray crystallography could radically improve our understanding of antibodies. The mapping of Ig-seq datasets to known antibody structures can indicate structurally, and perhaps functionally, uncharted areas. Furthermore, contrasting naïve and antigenically challenged datasets using structural antibody descriptors should provide insights into antibody maturation. As the number of antibody structures steadily increases and more and more Ig-seq datasets become available, the opportunities that arise from combining the two types of information increase as well. Here, we review how these data types enrich one another and show potential for advancing our knowledge of the immune system and improving antibody engineering.

Length-independent structural similarities enrich the antibody CDR canonical class model

Complementarity-determining regions (CDRs) are antibody loops that make up the antigen binding site. Here, we show that all CDR types have structurally similar loops of different lengths. Based on these findings, we created length-independent canonical classes for the non-H3 CDRs. Our length variable structural clusters show strong sequence patterns suggesting either that they evolved from the same original structure or result from some form of convergence. We find that our length-independent method not only clusters a larger number of CDRs, but also predicts canonical class from sequence better than the standard length-dependent approach.

To demonstrate the usefulness of our findings, we predicted cluster membership of CDR-L3 sequences from 3 next-generation sequencing datasets of the antibody repertoire (over 1,000,000 sequences). Using the length-independent clusters, we can structurally classify an additional 135,000 sequences, which represents a ∼20% improvement over the standard approach. This suggests that our length-independent canonical classes might be a highly prevalent feature of antibody space, and could substantially improve our ability to accurately predict the structure of novel CDRs identified by next-generation sequencing.

Enantioselective synthesis of sulfoxide using an SBA-15 supported vanadia catalyst: a computational elucidation using a QM/MM approach

Metal catalyzed asymmetric oxidation of prochiral sulfides is one of the prevailing strategies to produce enantiopure sulfoxides. Keeping in view the reported reactivity of peroxo vanadium complexes towards asymmetric oxidation reactions, this study explores the reactivity of vanadia represented as a VO₄ cluster with CH₃-S-Ph through DFT computations. The mechanism of the oxidation of sulfides to sulfoxides with unsupported VO₄ is thoroughly investigated. The chiral centre in the VO₄ cluster is introduced by grafting it on an SBA-15 support and two conformers of the supported cluster are thus obtained. The study was extended to locate transition states for the reaction of each conformer with CH₃-S-Ph. The large enantiomeric excess obtained from the energy difference of the transition states confirms the formation of enantiopure sulfoxide. Analysis of the computational results provides a rational explanation for the observed enantioselectivity, which is remarkable. The optical stability as well as asymmetry of chiral sulfoxides obtained by the current approach has been further confirmed by locating the planar transition state, through which conversion from one enantiomer to another takes place. The calculations suggest that transition between the two enantiomers of sulfoxide is hampered by sufficiently high inversion barriers.

Selection of nanobodies with broad neutralizing potential against primary HIV-1 strains using soluble subtype C gp140 envelope trimers

Broadly neutralizing antibodies (bnAbs) against HIV-1 protect from infection and reduce viral load upon therapeutic applications. However no vaccine was able so far to induce bnAbs demanding their expensive biotechnological production. For clinical applications, nanobodies (VHH) derived from heavy chain only antibodies from Camelidae, may be better suited due to their small size, high solubility/stability and extensive homology to human VH3 genes. Here we selected broadly neutralizing nanobodies by phage display after immunization of dromedaries with different soluble trimeric envelope proteins derived from HIV-1 subtype C. We identified 25 distinct VHH families binding trimeric Env, of which 6 neutralized heterologous primary isolates of various HIV-1 subtypes in a standardized in vitro neutralization assay. The complementary neutralization pattern of two selected VHHs in combination covers 19 out of 21 HIV-1 strains from a standardized panel of epidemiologically relevant HIV-1 subtypes. The CD4 binding site was preferentially targeted by the broadly neutralizing VHHs as determined by competition ELISAs and 3D models of VHH-Env complexes derived from negative stain electron microscopy. The nanobodies identified here are excellent candidates for further preclinical/clinical development for prophylactic and therapeutic applications due to their potency and their complementary neutralization patterns covering the majority of epidemiologically relevant HIV-1 subtypes.

Convergent immunological solutions to Argentine hemorrhagic fever virus neutralization

Transmission of hemorrhagic fever New World arenaviruses from their rodent reservoirs to human populations poses substantial public health and economic dangers. These zoonotic events are enabled by the specific interaction between the New World arenaviral attachment glycoprotein, GP1, and cell surface human transferrin receptor (hTfR1). Here, we present the structural basis for how a mouse-derived neutralizing antibody (nAb), OD01, disrupts this interaction by targeting the receptor-binding surface of the GP1 glycoprotein from Junín virus (JUNV), a hemorrhagic fever arenavirus endemic in central Argentina. Comparison of our structure with that of a previously reported nAb complex (JUNV GP1-GD01) reveals largely overlapping epitopes but highly distinct antibody-binding modes. Despite differences in GP1 recognition, we find that both antibodies present a key tyrosine residue, albeit on different chains, that inserts into a central pocket on JUNV GP1 and effectively mimics the contacts made by the host TfR1. These data provide a molecular-level description of how antibodies derived from different germline origins arrive at equivalent immunological solutions to virus neutralization.

The structure of a LAIR1-containing human antibody reveals a novel mechanism of antigen recognition

Antibodies are critical components of the human adaptive immune system, providing versatile scaffolds to display diverse antigen-binding surfaces. Nevertheless, most antibodies have similar architectures, with the variable immunoglobulin domains of the heavy and light chain each providing three hypervariable loops, which are varied to generate diversity. The recent identification of a novel class of antibody in humans from malaria endemic regions of Africa was therefore surprising as one hypervariable loop contains the entire collagen-binding domain of human LAIR1. Here, we present the structure of the Fab fragment of such an antibody. We show that its antigen-binding site has adopted an architecture that positions LAIR1, while itself being occluded. This therefore represents a novel means of antigen recognition, in which the Fab fragment of an antibody acts as an adaptor, linking a human protein insert with antigen-binding potential to the constant antibody regions which mediate immune cell recruitment.

DOI:http://dx.doi.org/10.7554/eLife.27311.001

When bacteria, viruses or parasites invade the human body, the immune system responds by producing proteins called antibodies. Antibodies recognize and bind to molecules (known as antigens) on the surface of the invaders. This binding can either neutralize the invader directly or trigger signals that cause other parts of the immune system to destroy it.

Our blood contains a huge range of different antibody molecules that each bind to a different antigen. This is despite most human antibodies having the same basic shape and structure. Six loops, known as complementarity determining regions (CDRs), emerge from the surface of the antibody to form the surface that recognizes the antigen. However, variations in the structure of the loops alter this surface enough to allow different antibodies to recognize completely different molecules.

In 2016, a new class of antibodies was identified. Unlike previously identified antibodies, these molecules had an entire human protein, called LAIR1, inserted into one of their CDR loops. Members of this group of antibodies bind to a molecule, known as a RIFIN, that is found on the surface of human red blood cells that are infected with the parasite that causes malaria.

How do LAIR1-containing antibodies bind to their RIFIN targets? Hsieh and Higgins investigated this question by using a technique called X-ray crystallography to determine the structure of the antibody. This revealed that instead of binding directly to an antigen, all of the six CDR loops in the LAIR1-containing antibody bind to the LAIR1 insert. By doing so, LAIR1 is oriented in a manner that enables it to bind to the RIFIN molecule from the parasite.

This is the first known example of an antibody that recruits another protein to bind to an antigen rather than binding directly to the pathogen itself. A future challenge will be to see if other antibodies exist that use this mechanism and whether it can be employed to design new therapeutic antibodies.

DOI:http://dx.doi.org/10.7554/eLife.27311.002

Antibody H3 Structure Prediction

Antibodies are proteins of the immune system that are able to bind to a huge variety of different substances, making them attractive candidates for therapeutic applications. Antibody structures have the potential to be useful during drug development, allowing the implementation of rational design procedures. The most challenging part of the antibody structure to experimentally determine or model is the H3 loop, which in addition is often the most important region in an antibody's binding site. This review summarises the approaches used so far in the pursuit of accurate computational H3 structure prediction.

Molecular basis for the mechanism of action of an anti-TACE antibody

Inhibitors of tumor necrosis factor-α converting enzyme (TACE) have potential as therapeutics for various diseases. Many small molecule inhibitors, however, exhibit poor specificity profiles because they target the highly conserved catalytic cleft of TACE. We report for the first time the molecular interaction of a highly specific anti-TACE antagonistic antibody (MEDI3622). We characterized the binding of MEDI3622 using mutagenesis, as well as structural modeling and docking approaches. We show that MEDI3622 recognizes a unique surface loop of sIVa-sIVb β-hairpin on TACE M-domain, but does not interact with the conserved catalytic cleft or its nearby regions. The exquisite specificity of MEDI3622 is mediated by this distinct structural feature on the TACE M-domain. These findings may aid the design of antibody therapies against TACE.

abYsis: Integrated Antibody Sequence and Structure-Management, Analysis, and Prediction

abYsis is a web-based antibody research system that includes an integrated database of antibody sequence and structure data. The system can be interrogated in numerous ways-from simple text and sequence searches to sophisticated queries that apply 3D structural constraints. The publicly available version includes pre-analyzed sequence data from the European Molecular Biology Laboratory European Nucleotide Archive (EMBL-ENA) and Kabat as well as structure data from the Protein Data Bank. A researcher's own sequences can also be analyzed through the web interface. A defining characteristic of abYsis is that the sequences are automatically numbered with a series of popular schemes such as Kabat and Chothia and then annotated with key information such as complementarity-determining regions and potential post-translational modifications. A unique aspect of abYsis is a set of residue frequency tables for each position in an antibody, allowing "unusual residues" (those rarely seen at a particular position) to be highlighted and decisions to be made on which mutations may be acceptable. This is especially useful when comparing antibodies from different species. abYsis is useful for any researcher specializing in antibody engineering, especially those developing antibodies as drugs. abYsis is available at www.abysis.org.

MoFvAb: Modeling the Fv region of antibodies

Knowledge of the 3-dimensional structure of the antigen-binding region of antibodies enables numerous useful applications regarding the design and development of antibody-based drugs. We present a knowledge-based antibody structure prediction methodology that incorporates concepts that have arisen from an applied antibody engineering environment. The protocol exploits the rich and continuously growing supply of experimentally derived antibody structures available to predict CDR loop conformations and the packing of heavy and light chain quickly and without user intervention. The homology models are refined by a novel antibody-specific approach to adapt and rearrange sidechains based on their chemical environment. The method achieves very competitive all-atom root mean square deviation values in the order of 1.5 Å on different evaluation datasets consisting of both known and previously unpublished antibody crystal structures.

Structural diversity in a human antibody germline library

To support antibody therapeutic development, the crystal structures of a set of 16 germline variants composed of 4 different kappa light chains paired with 4 different heavy chains have been determined. All four heavy chains of the antigen-binding fragments (Fabs) have the same complementarity-determining region (CDR) H3 that was reported in an earlier Fab structure. The structure analyses include comparisons of the overall structures, canonical structures of the CDRs and the VH:VL packing interactions. The CDR conformations for the most part are tightly clustered, especially for the ones with shorter lengths. The longer CDRs with tandem glycines or serines have more conformational diversity than the others. CDR H3, despite having the same amino acid sequence, exhibits the largest conformational diversity. About half of the structures have CDR H3 conformations similar to that of the parent; the others diverge significantly. One conclusion is that the CDR H3 conformations are influenced by both their amino acid sequence and their structural environment determined by the heavy and light chain pairing. The stem regions of 14 of the variant pairs are in the ‘kinked’ conformation, and only 2 are in the extended conformation. The packing of the VH and VL domains is consistent with our knowledge of antibody structure, and the tilt angles between these domains cover a range of 11 degrees. Two of 16 structures showed particularly large variations in the tilt angles when compared with the other pairings. The structures and their analyses provide a rich foundation for future antibody modeling and engineering efforts.

Antibody Structure

A brief outline of antibody structure is followed by highlights from several recently determined crystal structures of human, antiviral Fabs. These Fabs all have novel structural features that allow them to potently and broadly neutralize their targets.

The diversity of H3 loops determines the antigen-binding tendencies of antibody CDR loops

Of the complementarity-determining regions (CDRs) of antibodies, H3 loops, with varying amino acid sequences and loop lengths, adopt particularly diverse loop conformations. The diversity of H3 conformations produces an array of antigen recognition patterns involving all the CDRs, in which the residue positions actually in contact with the antigen vary considerably. Therefore, for a deeper understanding of antigen recognition, it is necessary to relate the sequence and structural properties of each residue position in each CDR loop to its ability to bind antigens. In this study, we proposed a new method for characterizing the structural features of the CDR loops and obtained the antigen-binding ability of each residue position in each CDR loop. This analysis led to a simple set of rules for identifying probable antigen-binding residues. We also found that the diversity of H3 loop lengths and conformations affects the antigen-binding tendencies of all the CDR loops.

Augmented Binary Substitution: Single-pass CDR germ-lining and stabilization of therapeutic antibodies

Although humanized antibodies have been highly successful in the clinic, all current humanization techniques have potential limitations, such as: reliance on rodent hosts, immunogenicity due to high non-germ-line amino acid content, v-domain destabilization, expression and formulation issues. This study presents a technology that generates stable, soluble, ultrahumanized antibodies via single-step complementarity-determining region (CDR) germ-lining. For three antibodies from three separate key immune host species, binary substitution CDR cassettes were inserted into preferred human frameworks to form libraries in which only the parental or human germ-line destination residue was encoded at each position. The CDR-H3 in each case was also augmented with 1 ± 1 random substitution per clone. Each library was then screened for clones with restored antigen binding capacity. Lead ultrahumanized clones demonstrated high stability, with affinity and specificity equivalent to, or better than, the parental IgG. Critically, this was mainly achieved on germ-line frameworks by simultaneously subtracting up to 19 redundant non-germ-line residues in the CDRs. This process significantly lowered non-germ-line sequence content, minimized immunogenicity risk in the final molecules and provided a heat map for the essential non-germ-line CDR residue content of each antibody. The ABS technology therefore fully optimizes the clinical potential of antibodies from rodents and alternative immune hosts, rendering them indistinguishable from fully human in a simple, single-pass process.

Defining the complementarities between antibodies and haptens to refine our understanding and aid the prediction of a successful binding interaction

BACKGROUND

Low molecular weight haptens (<1000 Da) cannot be recognized by the immune system unless conjugated to larger carrier molecules. Antibodies to these exceptionally small antigens can still be generated with exquisite sensitivity. A detailed understanding at the molecular level of this incredible ability of antibodies to recognize haptens, is still limited compared to other antigen classes.

METHODS

Different hapten targets with a broad range of structural flexibility and polarity were conjugated to carrier proteins, and utilized in sheep immunization. Three antibody libraries were constructed and used as potential pools to isolate specific antibodies to each target. The isolated antibodies were analysed in term of CDR length, canonical structure, and binding site shape and electrostatic potential.

RESULTS

The simple, chemically naïve structure of squalane (SQA) was recognized with micromolar sensitivity. An increase in structural rigidity of the hydrophobic and cyclic coprostane (COP) did not improve this binding sensitivity beyond the micromolar range, whilst the polar etioporphyrin (POR) was detected with nanomolar sensitivity. Homoserine lactone (HSL) molecules, which combine molecular flexibility and polarity, generated super-sensitive (picomolar) interactions. To better understand this range of antibody-hapten interactions, analyses were extended to examine the binding loop canonical structures and CDR lengths of a series of anti-hapten clones. Analyses of the pre and post- selection (panning of the phage displayed libraries) sequences revealed more conserved sites (123) within the post-selection sequences, when compared to their pre-selection counterparts (28). The strong selection pressure, generated by panning against these haptens resulted in the isolation of antibodies with significant sequence conservation in the FW regions, and suitable binding site cavities, representing only a relatively small subset of the available full repertoire sequence and structural diversity. As part of this process, the important influence of CDR H2 on antigen binding was observed through its direct interaction with individual antigens and indirect impact on the orientation and the pocket shape, when combined with CDRs H3 and L3. The binding pockets also displayed electrostatic surfaces that were complementary to the hydrophobic nature of COP, SQA, and POR, and the negatively charged HSL.

CONCLUSIONS

The best binding antibodies have shown improved capacity to recognize these haptens by establishing complementary binding pockets in terms of size, shape, and electrostatic potential.